Adolescent ; Adult ; Female ; Fracture Fixation, Internal ; Humans ; Male ; Middle Aged ; Multiple Trauma ; diagnosis ; surgery ; Spinal Fractures ; diagnosis ; surgery ; Treatment Outcome ; Young Adult

Purpose:To clarify the diagnosis and management of ureteral obstruction owing to vena cava orcongenital crossing vessels. Methods: Preoperative sonography, intavenous urography (IVU), retrograde urogra-phy or magnetic resonance urography(MRU) were performed in 19 cases of patients for evaluation of hy-droureteronepherosis. Combined with magnetic resonance imaging(MRI) or cavography, retrocaval ureter couldbe detected. Colour Doppler imaging was used to detect crossing vessels. During operations, retrocaval (8cases) or retroiliac (1 cases) ureters were excised, crossing vessels (10 cases) were divided then ureteroureteralanastomosis or dismembered pyeloplasty (Anderson-Hynes) were completed. Results:3 to 6 months after opera-tions, hydroureteronepherosis was lightened to different extends in all patients. After median follow-up of 15.7months (range 1 to 4.5 years), hydroureteronepherosis was found in one patient. Conclusions:Disorder of bloodvessels should be considered in the differential diagnosis of extrinsic ureteral obstruction. Sonography, IVU,MRI combined with cavography, color Doppler imaging are of great value in the diagnosis of those conditions.Early diagnosis and treatment are very important.

Objective: To investigate the clinicopathological features, treatment and prognosis of duodenal-type follicular lymphoma. Methods: Four cases of duodenal-type follicular lymphoma diagnosed at Guangdong General Hospital from 2014 to 2015 with detailed clinical data were included. The histomorphology, immunophenotype, treatment and prognoses were analyzed. Results: The patients′ age ranged from 51 to 57 years (mean 54 years), and there were 2 males and 2 females. The involved sites were gastric fundus in one case, second portion of the duodenum in two cases and terminal ileum in one case. All patients presented with multiple mucosal granules or nodules at endoscopy. Microscopically, there were multiple mucosal neoplastic follicles, constituting grade 1-2 disease based on nodal follicular lymphoma grading system. The tumor cells were positive for CD20, CD10, bcl-6 and bcl-2. CD21 highlighted the follicular dendritic meshwork mainly at the periphery of the follicles. Proliferation index was low. Three patients received rituximab monotherapy for 4 cycles, leading to complete remission. One patient refused therapy and the disease progressed to systemic lymphoma 15 months after the initial diagnosis. Conclusions Duodenal-type follicular lymphoma is a special variant of follicular lymphoma with indolent clinical course. The tumor exhibits morphology of low grade follicular lymphoma with characteristic dendritic meshwork at the periphery of the follicles and a low proliferation index. Prognosis is excellent. Rituximab monotherapy is treatment of choice, but a small minority of patients may progress to systemic disease.

Objective:Based on radiomics characteristics, different machine learning classification models are constructed to predict the gamma pass rate of dose verification in intensity-modulated radiotherapy for pelvic tumors, and to explore the best prediction model.Methods:The results of three-dimensional dose verification based on phantom measurement were retrospectively analyzed in 196 patients with pelvic tumor intensity-modulated radiotherapy plans. The gamma pass rate standard was 3%/2 mm and 10% dose threshold. Prediction models were constructed by extracting radiomic features based on dose documentation. Four machine learning algorithms, random forest, support vector machine, adaptive boosting, and gradient boosting decision tree were used to calculate the AUC value, sensitivity, and specificity respectively. The classification performance of the four prediction models was evaluated.Results:The sensitivity and specificity of the random forest, support vector machine, adaptive boosting, and gradient boosting decision tree models were 0.93, 0.85, 0.93, 0.96, 0.38, 0.69, 0.46, and 0.46, respectively. The AUC values were 0.81 and 0.82 for the random forest and adaptive boosting models, respectively, and 0.87 for the support vector machine and gradient boosting decision tree models.Conclusions:Machine learning method based on radiomics can be used to construct a prediction model of gamma pass rate for specific dosimetric verification of pelvic intensity-modulated radiotherapy. The classification performance of the support vector machine model and gradient boosting decision tree model is better than that of the random forest model and adaptive boosting model.

OBJECTIVETo investigate the clinical effects of internal fixation with double endobutton for the treatment of acromioclavicular joint dislocation of Tossy Grade III.

METHODSFrom 2007.7 to 2008.12, 27 patients with acromioclavicular joint dislocation of Tossy Grade III were fixed with double endobutton. Among the patients, 17 patients were male and 10 patients were female, with an average age of (35.0 +/- 1.3) years (ranged from 23 to 60 years). Fourteen patients were injured by traffic accident, 6 patients were work-related injuries, 4 patients were sports injuries, and 3 patients were injured by falling down. Sixteen patients had injuries in the left, and 11 patients in the right. All the patients were Tossy III type dislocation without clavicle fracture. The therapeutic effects were evaluated by Karlsson criteria based on range of motion of acromioclavicular joint, pain, muscle force and postreduction X-ray.

RESULTSAll the patients were followed up for 6 to 14 months, mean 10.2 months. According to the Karlsson score criteria, 24 patients obtained an excellent result, 2 fair and 1 poor.

CONCLUSIONFixation with double endobutton is to be a new method for the treatment of acromioclavicular joint dislocation, which has the advantages of minimal trauma, reliable fixation, early functional rehabilitation and so on.

Acromioclavicular Joint ; injuries ; surgery ; Adult ; Female ; Fracture Fixation, Internal ; methods ; Humans ; Internal Fixators ; Male ; Middle Aged ; Postoperative Complications ; Shoulder Dislocation ; surgery ; Treatment Outcome ; Young Adult

Objective: To evaluate the expression of βF1 and T cell receptor (TCR)γ in T lymphoblastic lymphoma/leukemia(T-LBL/ALL), and investigate the clinicopathological features. Methods: Fifty-one cases of T-LBL/ALL were collected at Guangdong General Hospital from 2010 to 2016, the expression of βF1 and TCRγ was assessed by immunohistochemistry. Results: There were 13 cases of children and adolescents, and 38 cases of adults. The expression rates of βF1 and TCRγ were 27.5%(14/51) and 15.7%(8/51) respectively. The proportion of adults in αβ T-LBL/ALL, TCR-silent T-LBL/ALL and γδ T-LBL/ALL was 7/14, 79.3%(23/29)and 8/8 respectively, and the difference was significant (P=0.023). There was no statistical difference in sex, LDH, bone marrow involvement and Ann arbor stage among these three groups(P>0.05). γδ T-LBL/ALLs included 6 cases of CD4^-/CD8^- phenotype, whereas αβ T-LBL/ALL included 7 cases of CD4⁺ /CD8⁺ phenotype. There was significant difference in CD4/CD8 expression among these three groups(P<0.01). Conclusions γδ T-LBL/ALL occurred only in adults, with predominantly CD4^-/CD8^- phenotype. αβ T-LBL/ALL occurred more common in children and adolescents, with predominantly CD4⁺ /CD8⁺ phenotype.

Objective:To study the expression of phosphates signal transducer and activator of transcription 3 (pSTAT3) and programmed death ligand-1 (PD-L1) in extranodal NK/T cell lymphomas (ENKTCL) and the relationships of pSTAT3 and PD-L1 expression with the clinicopathological characteristics and prognosis of ENKTCL.Methods:Fifty-one cases of ENKTCL diagnosed at Guangdong Provincial People′s Hospital from June 2015 to February 2019 were included in the study. The expression of pSTAT3 and PD-L1 was examined using immunohistochemistry.Results:There were 35 males and 16 females, ranging from 18 to 85 years old with a median age of 47 years. The positive rates of pSTAT3 and PD-L1 expression were 68.6% (35/51) and 76.5% (39/51), respectively. pSTAT3 expression was correlated with PD-L1 expression ( P=0.033, R=0.322), while there were no associations of pSTAT3 and PD-L1 expression with the clinicopathological characteristics of ENKTCL, including age, sex, clinical site, B symptom, Ann Arbor stage, LDH value, EBV DNA load of peripheral blood and international proliferation index score. Kaplan-Meier survival analysis showed the prognoses of the pSTAT3 and PD-L1 positive groups were slightly better than the respective negative groups, but the differences were not significantly ( P>0.05). Conclusions:pSTAT3 is highly expressed in extranodal NK/T cell lymphoma and related to the expression of PD-L1, which provides a potential target and rationale for combinations of targeted therapies and immune checkpoint blockade inhibitors in the treatment of ENKTCL.

Objective:To explore the feasibility of a classification prediction model for gamma pass rates (GPRs) under different intensity-modulated radiation therapy techniques for pelvic tumors using a radiomics-based machine learning approach, and compare the classification performance of four integrated tree models.Methods:With a retrospective collection of 409 plans using different IMRT techniques, the three-dimensional dose validation results were adopted based on modality measurements, with a GPR criterion of 3%/2 mm and 10% dose threshold. Then prediction were built models by extracting radiomics features based on dose documentation. Four machine learning algorithms were used, namely random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). Their classification performance was evaluated by calculating sensitivity, specificity, F1 score, and AUC value. Results:The RF, AdaBoost, XGBoost, and LightGBM models had sensitivities of 0.96, 0.82, 0.93, and 0.89, specificities of 0.38, 0.54, 0.62, and 0.62, F1 scores of 0.86, 0.81, 0.88, and 0.86, and AUC values of 0.81, 0.77, 0.85, and 0.83, respectively. XGBoost model showed the highest sensitivity, specificity, F1 score, and AUC value, outperforming the other three models. Conclusions:To build a GPR classification prediction model using a radiomics-based machine learning approach is feasible for plans using different intensity-modulated radiotherapy techniques for pelvic tumors, providing a basis for future multi-institutional collaborative research on GPR prediction.

Objective:To explore the feasibility and validity of constructing an intensity-modulated radiotherapy gamma pass rate prediction model after combining the SHAP values with the extreme gradient boosting tree (XGBoost) algorithm feature selection technique, and to deliver corresponding model interpretation.Methods:The dose validation results of 196 patients with pelvic tumors receiving fixed-field intensity-modulated radiotherapy using modality-based measurements with a gamma pass rate criterion of 3%/2 mm and 10% dose threshold in Hunan Provincial Tumor Hospital from November 2020 to November 2021 were retrospectively analyzed. Prediction models were constructed by extracting radiomic features based on dose files and using SHAP values combined with the XGBoost algorithm for feature filtering. Four machine learning classification models were constructed when the number of features was 50, 80, 110 and 140, respectively. The area under the receiver operating characteristic curve (AUC), recall rate and F1 score were calculated to assess the classification performance of the prediction models.Results:The AUC of prediction model constructed with 110 features selected based on the SHAP-valued features was 0.81, the recall rate was 0.93 and the F1 score was 0.82, which were all better than the other 3 models.Conclusion:For intensity-modulated radiotherapy of pelvic tumor, SHAP values can be used in combination with the XGBoost algorithm to select the optimal subset of radiomic features to construct predictive models of gamma pass rates, and deliver an interpretation of the model output by SHAP values, which may provide value in understanding the prediction by machine learning-dependent models.

Objectives: To investigate the clinicopathological features, therapy and prognosis of primary cardiac CD5-positive diffuse large B-cell lymphoma with C-MYC and bcl-2 double expression. Methods: Two cases diagnosed at Guangdong Provincial People′s Hospital were included, the clinical data were collected; the tumor morphology, immunophenotypic profiles, therapy and prognosis were analyzed. Results: Case 1 was a 55-year-old man and case 2 was a 61-year-old women. Intraoperatively, both cases showed large masses in the right atrium or ventricle, involving adjacent tissue. Pathologically, the tumors were composed of diffusely infiltrating large lymphoid cells with high mitotic activity and apoptosis. The tumor cells were positive for CD20, CD5, bcl-6, MUM1, C-MYC and bcl-2, and the Ki-67 index was equal or greater than 90%. Case 1 had bcl-6, but not bcl-2 or MYC gene rearrangements. No MYC, bcl-2 or bcl-6 gene rearrangements were detected in case 2. Case 1 defaulted chemotherapy after operation and died 1 month after diagnosis. Case 2 was treated with 4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) therapy after surgery and attained partial remission, and was then treated with apatinib and ibrutinib, and remained stable 18 months after initial diagnosis. Conclusion Primary cardiac CD5-positive diffuse large B-cell lymphoma with C-MYC and bcl-2 double expression usually shows large infiltrative mass in the right atrium or ventricle, non-germinal center like immunophenotype and high proliferation index, and this may contribute to the aggressiveness of primary cardiac lymphoma.